Servo actuator and fast self-tuning method of gain for using the same

ABSTRACT

A fast self-tuning method of gain applied to a servo actuator connected with a motor is disclosed and includes following steps: retrieving a current-feedback information of the motor to compute a torque estimated value; retrieving a position-feedback information of the motor to compute an acceleration estimated value; computing a system inertia based on the torque estimated value and the acceleration estimated value, wherein the system inertia indicates an inertia of the motor carrying a specific load; computing an estimated control gain for the servo actuator based on the system inertia; and, performing a self-tuning procedure by the servo actuator in accordance with the estimated control gain.

CROSS-REFERENCE TO RELATED APPLICATION

This patent application claims the benefit of U.S. Provisional PatentApplication No. 63/302,689, filed Jan. 25, 2022, which is incorporatedby reference herein.

BACKGROUND OF THE DISCLOSURE Technical Field

The present disclosure relates to a servo actuator, and specifically toa servo actuator that may automatically tune the control gain, and to aself-turning method used by the servo actuator.

Description of Related Art

Industrial machines use one or more motors to carry loads to work, andeach of the machines is configured with one or more servo actuators torespectively control these motors. The servo actuator records multipleparameters; however, users usually don't know how to set theseparameters for the machines to operate more stably.

Generally, the machine may be configured with an automatic gain tuningfunction (also called as an auto-tuning function) in order to assist theuser to set the aforementioned parameters. The automatic gain tuningfunction is written to be the computer software as the process based onexpert's experiences. Or, the automatic gain tuning function is recordeddirectly in the servo actuator. According to the automatic gain tuningfunction, users who aren't familiar with the machine may be guided bythe user interface (UI) on the computer or the servo actuator and thenperform such processes step-by-step to set the gain(s) of the servoactuator. By using the above function, only few machines that cannot beprocessed through the automatic gain tuning function need professionalsto go to the scene in order to solve the problem. As a result, the hugelabor costs may be reduced.

As mentioned above, in order for the users to perform setting to themachines, the auto tuning function of the related art is usually usedincorporated with computer software to generate the UI that may guidethe user to perform the setting. In that case, a part of environments(such as dust-free rooms) that are forbidden to use computer is unableto implement the auto tuning function. Also, some environments havingthe computer equipment that are forbidden to install software due toinformation security are unable to implement the auto tuning function aswell.

Besides, the automatic gain tuning function of the related art usuallycontrols the machine to enable a controlled component to move betweentwo points. In order to do so, a motor of the machine needs to rotatefor at least one to three circles. For machines (such as robotic arms)that have a controlled component having different characteristics atdifferent positions or machines that may control the controlledcomponent to move only for a very short distance, but it cannotimplement this type of automatic gain tuning function.

The approach that a machine enables its controlled component to movebetween two points needs two to three minutes to finish the entire gaintuning procedure. For some industrial environments, this kind of gaintuning procedure is lack of efficiency.

SUMMARY OF THE DISCLOSURE

The present disclosure is directed to a servo actuator and a fastself-tuning method of gain used by the servo actuator, which maycomplete a gain tuning procedure for the servo actuator in a very shorttime and only require a slight movement of the motor while executing thegain tuning procedure.

In one of the exemplary embodiments, the fast self-tuning method of gainis applied by an actuator connected with a motor and includes followingsteps:

a) retrieving a current feedback signal of the motor and computing atorque estimated value based on the current feedback signal;

b) retrieving a position feedback signal of the motor and computing anacceleration estimated value based on the position feedback signal;

c) computing a system inertia in accordance with the torque estimatedvalue and the acceleration estimated value, wherein the system inertiais an inertia of the motor carrying a load;

d) computing an estimated control gain in accordance with a no-loadinertia of the motor and the system inertia; and

e) tuning the actuator by using the estimated control gain.

In one of the exemplary embodiments, the servo actuator is electricallyconnected with a motor, the motor carries a load, and a controlledsystem is formed by the motor and the load. The servo actuator includes:

a current detecting component, receiving an exciting current of themotor and generating a current feedback signal;

a central processing unit (CPU), electrically connected with the currentdetecting component and the motor, and comprising:

a torque estimating module, computing a torque estimated value based onthe current feedback signal;

an acceleration estimating module, receiving a position feedback signalof the motor and computing an acceleration estimated value based on theposition feedback signal;

a gain computing module, computing a system inertia correspondinglybased on the torque estimated value and the acceleration estimatedvalue, and computing an estimated control gain based on a no-loadinertia of the motor and the system inertia, wherein the system inertiais an inertia of the motor carrying the load; and a controlling module,tuning the servo actuator based on the estimated control gain; and

a storage, connected with the CPU, recording a data array including thetorque estimated value and the acceleration estimated value, and the CPUis configured to read the data array to obtain the torque estimatedvalue and the acceleration estimated value.

In comparison with related art, the present disclosure may automaticallycomplete the gain tuning procedure after the servo actuator isactivated, wherein the execution time of the gain tuning procedure isshort without requiring a large degree of movement of the motor, and itis unnecessary to store a large amount of data for the execution of thegain tuning procedure.

DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a servo actuator system of an embodimentaccording to the present disclosure.

FIG. 2 is a flowchart of a tuning method of an embodiment according tothe present disclosure.

FIG. 3 is a schematic diagram showing an inertia of an embodimentaccording to the present disclosure.

FIG. 4 is a control gain setting flowchart of an embodiment according tothe present disclosure.

FIG. 5 is a flowchart for determining stability of an embodimentaccording to the present disclosure.

FIG. 6 is an inertia estimating flowchart of an embodiment according tothe present disclosure.

FIG. 7 is a schematic diagram showing a control architecture of anembodiment according to the present disclosure.

FIG. 8 is a schematic diagram showing frequency response of anembodiment according to the present disclosure.

DETAILED DESCRIPTION OF THE DISCLOSURE

In cooperation with the attached drawings, the technical contents anddetailed description of the present disclosure are described hereinafteraccording to multiple embodiments, being not used to limit its executingscope. Any equivalent variation and modification made according toappended claims is all covered by the claims claimed by the presentdisclosure.

Please refer to FIG. 1 and FIG. 2 , wherein FIG. 1 is a block diagram ofa servo actuator system of an embodiment according to the presentdisclosure and FIG. 2 is a flowchart of a tuning method of an embodimentaccording to the present disclosure. FIG. 1 discloses a servo actuatorsystem, wherein the servo actuator system includes a servo actuator(referred to as the actuator 1 hereinafter) and a controlled systemelectrically connected with the actuator 1. The controlled system atleast includes a motor 2 electrically connected with the actuator 1 anda load 3 carried by the motor 2.

One technical feature of the present disclosure is that, after theactuator 1 is activated or the actuator 1 accepts the setting from theuser to activate an automatic gain tuning function (also called asauto-tuning function), the actuator 1 may automatically perform tuningfor internal control gain(s) aimed at the controlled system currentlyconnected therewith. After being controlled by the actuator 1, thecontrolled system may operate stably.

In one embodiment, a user may use a user interface (UI) or other mediato set an auto-tuning parameter(s) of the actuator 1 (for example, toenable a internal flag of the actuator 1). When the actuator 1 detectsthat the auto-tuning parameter is enabled, it may automatically detectthe status of the controlled system currently connected therewith, andthe actuator 1 may perform the fast self-tuning method of gain of thepresent disclosure to implement the automatic gain tuning function.

As disclosed in FIG. 1 , the actuator 1 of the present disclosure atleast includes a central processing unit (CPU) 11, a current detectingcomponent 12, a storage 13, and a power outputting component 14, whereinthe current detecting component 12, the storage 13, and the poweroutputting component 14 are electrically connected with the CPU 11.

In the present disclosure, the CPU 11 records firmware, and the firmwareis virtually divided into a controlling module 111, a torque estimatingmodule 112, an acceleration estimating module 113, and a gain computingmodule 114 based on the functions executed by the CPU 11. In otherwords, the controlling module 111, the torque estimating module 112, theacceleration estimating module 113, and the gain computing module 114are firmware modules implemented by the firmware of the CPU 11. In thepresent disclosure, the CPU 11 uses the gain computing module 114 tocompute a control gain correspondingly in according to the status of thecontrolled system and to automatically tune the actuator 1 based on thecomputed control gain (detailed described in the following).

The motor 2 at least includes a driver unit 21 and a position detectingcomponent 22, and the motor 2 directly connects to a load 3 orindirectly connects to the load 3 through a linking device (such as abelt or a connecting rod, etc.). In one embodiment, the actuator 1connects to the motor 2 through the CPU 11, the current detectingcomponent 12, and the power outputting component 14. As shown in FIG. 1, the CPU 11 sends a voltage command C to the power outputting component14, and the power outputting component 14 generates a motor voltage Ucorrespondingly based on the voltage command C and outputs the motorvoltage U to the motor 2 in order to control the motor 2.

The motor 2 receives the motor voltage U from the actuator 1 through thedriver unit 21, and the motor 2 is driven by the driver unit 21 torotate. After rotating, the motor 2 may bring the load 3 to operate. Themotor 2 detects and records a position feedback signal X of the motor 2through the position detecting component 22 and transmits the positionfeedback signal X back to the actuator 1. Also, the motor 2 transmits anexciting current I′ to the actuator 1 through the driver unit 21. Theactuator 1 receives the exciting current I′ from the motor 2 through thecurrent detecting component 12, and then generates a current feedbacksignal I correspondingly based on the exciting current I′.

Please refer to FIG. 1 and FIG. 2 at the same time, wherein FIG. 2 is aflowchart of a tuning method of an embodiment according to the presentdisclosure. FIG. 2 discloses specific steps of the fast self-tuningmethod of gain of the present disclosure (referred to as the tuningmethod hereinafter). The tuning method is substantially applied to theactuator 1 as shown in FIG. 1 .

In the disclosure, the actuator 1 has multiple configurable and tunableparameters, and the multiple parameters include one auto-tuningparameter. In order for the actuator 1 to execute the tuning method ofthe present disclosure to implement the automatic gain tuning function,a user needs to enable the auto-tuning parameter of the actuator 1 byusing an UI (not shown). After an enabled auto-tuning parameter isdetected, the actuator 1 may automatically input a sine wave currentcorresponding to a single frequency sine wave to the controlled system,so as to perturb the controlled system and then obtain a correspondinginformation from the controlled system (step S10). Therefore, theactuator 1 may perform the tuning method of the present disclosure basedon the obtained information.

After receiving the sine wave current, the motor 2 may perform a slightmovement; meanwhile, the actuator 1 may receive an exciting currentoutputted from the motor 2, and the current detecting component 12 maygenerate a current feedback signal correspondingly based on the excitingcurrent (step S12). Also, the actuator 1 retrieves the current feedbacksignal through the torque estimating module 112 of the CPU 11 andcomputes a torque estimated value based on the current feedback signal(step S14).

After the motor 2 moves, the actuator 1 may also receive a positionfeedback signal outputted from the motor 2 through the accelerationestimated module 113 of the CPU 11, and the actuator 1 may compute anacceleration estimated value based on the position feedback signal (stepS16).

As mentioned above, the controlled system in the embodiment includes themotor 2 and the load 3 carried by the motor 2. The aforementioned torqueestimated value indicates the torque generated by the motor 2 when themotor 2 moves with the load 3, and the aforementioned accelerationestimated value indicates the acceleration generated by the motor 2 whenthe motor 2 moves with the load 3. Besides, the step S12, the step S14,and the step S16 do not have a fixed execution order. In particular, theCPU 11 may compute the torque estimated value and the accelerationestimated value based on an arbitrary order; otherwise, the CPU 11 maycompute the torque estimated value and the acceleration estimated valueat the same time by way of multiplexing, and not limited to theexecution order as shown in FIG. 2 .

After the step S14 and the step S16, the actuator 1 obtains the torqueestimated value and the acceleration estimated value through the gaincomputing module 114 of the CPU 11 and uses the gain computing module114 to compute a system inertia correspondingly based on the torqueestimated value and the acceleration estimated value (step S18). Inparticular, the system inertia of the embodiment indicates an inertia ofthe motor 2 while carrying the load 3. Be more specific, the systeminertia is the weight of load 3 currently carried by the motor 2.

In one embodiment, the gain computing module 114 may compute the systeminertia in accordance with a first formula:

${J = \frac{T}{\alpha}},$

wherein J indicates the system inertia, T indicates the torque estimatedvalue, and a indicates the acceleration estimated value. However, theabove description is only one of the exemplary embodiments of thepresent disclosure, but not limited thereto.

It should be mentioned that the actuator 1 may include a storage 13connected with the CPU 11. The storage 13 may be, for example but notlimited to, any kind of memory.

In one embodiment, the torque estimating module 112 stores the computedtorque estimated value to the storage 13 after the step S14 and theacceleration estimating module 113 stores the computed accelerationestimated value to the storage 13 after the step S16. In the embodiment,the storage 113 stores a data array (such as a data array M as disclosedin FIG. 1 ) recording the torque estimated value and the accelerationestimated value. In the step S18, the gain computing module 114 of theCPU 11 may inquire the data array M in the storage 113 to obtain thetorque estimated value and the acceleration estimated value and thencompute the system inertia in accordance with the torque estimated valueand the acceleration estimated value.

Please refer to FIG. 3 at the same time, wherein FIG. 3 is a schematicdiagram showing an inertia of an embodiment according to the presentdisclosure. As mentioned above, the CPU 11 of the present disclosurecomputes the system inertia based on the torque estimated value and theacceleration estimated value. Because the system inertia is computedbased on values that are estimated, the system inertia being computedmay have an error.

In the embodiment of FIG. 3 , the actuator 1 causes the motor 2 to moveby inputting the sine wave current, and the CPU 11 obtains multipletorque estimated values and multiple acceleration estimated valuesrespectively at multiple time points while the motor 2 moves. In theembodiment, the gain computing module 114 of the CPU 11 may execute afirst-order linear regression calculation in accordance with the torqueestimated values and the acceleration estimated values of the multipletime points to generate a regression line. Therefore, the gain computingmodule 114 of the CPU 11 may regard the slope of the regression line asthe system inertia of the controlled system.

For example, the sine wave current may be corresponding to a singlefrequency sine wave with a frequency of 5 Hz, which means thecorresponding time of the single frequency sine wave is 200 ms. In theembodiment, the CPU 11 may compute one torque estimated value and oneacceleration estimated value in every 20 ms after the sine wave currentis inputted; therefore, the CPU 11 may compute the system inertia of thecontrolled system based on ten torque estimated values and tenacceleration estimated values. However, the above time and amount areonly presented for an instance, but not intended to limit the scope ofthe invention.

The present disclosure executes the first-order liner regressioncalculation based on multiple torque estimated values and multipleacceleration estimated values to compute the system inertia, so that thesystem inertia may be computed more accurate. Besides, it is unnecessaryfor the actuator 1 to store a large amount of data just for thecomputation of the system inertia. As a result, it is unnecessary forthe actuator 1 to arranged a huge memory. Since no huge storage space isunnecessary, the present disclosure may use the actuator 1 directly toimplement the self-tuning procedure of the control gain withoutadditional computer equipment.

Please refer back to FIG. 2 . After the step S18, the gain computingmodule 114 may compute an estimated control gain (such as the estimatedcontrol gain N as disclosed in FIG. 1 ) correspondingly based on ano-load inertia of the motor 2 and the computed system inertia (stepS20) and provide the estimated control gain to the controlling module111. In one embodiment, the estimated control gain may, for example butnot limited to, include a position gain used by a position controller116 (as shown in the FIG. 7 ) of the actuator 1 and a velocity gain usedby a velocity controller 117 (as shown in the FIG. 7 ) of the actuator1.

In particular, the no-load inertia of the motor 2 is fixed after themotor 2 is manufactured, so the no-load inertia of the motor 2 belongsto one of the known information of the actuator 1. Accordingly, the gaincomputing module 114 may compute each parameter (i.e., an estimatedcontrol gain(s)) that the actuator 1 should apply based on the no-loadinertia of the motor 2 and the system inertia being estimated, so thatthe actuator 1 may control the controlled system to move stably.

Please refer to FIG. 4 at the same time, wherein FIG. 4 is a controlgain setting flowchart of an embodiment according to the presentdisclosure. FIG. 4 is presented to further interpret the step S20 ofFIG. 2 .

In one embodiment, the actuator 1 may internally create a bandwidthcorrespondence table (not shown), and the bandwidth correspondence tablepreviously records multiple expected bandwidths respectivelycorresponding to different system inertias, wherein each of the systeminertias is inversely proportional to its corresponding expectedbandwidth. In other words, the smaller the system inertia, the biggerthe expected bandwidth is. The bigger the system inertia, the smallerthe expected bandwidth is. For example, the bandwidth correspondencetable may record that a first load with a ten-time inertia correspondsto an expected bandwidth of 100 Hz and a second load with a hundred-timeinertia corresponds to an expected bandwidth of 10 Hz. However, theabove descriptions are only few embodiments of the present disclosure,but not limited thereto.

In the embodiment, the gain computing module 114 first obtains thesystem inertia estimated in the step S18 (step S30), and then inquiresthe bandwidth correspondence table based on the system inertia (stepS32). Therefore, an expected bandwidth corresponding to the systeminertia may be obtained from the bandwidth correspondence table (stepS34). Besides, the gain computing module 114 may decide an estimatedcontrol gain to be used by the actuator 1 in accordance with theexpected bandwidth (step S36). In other words, the estimated controlgain being used to tune the actuator 1 in the present disclosure isdirectly related to the expected bandwidth corresponding to the systeminertia of the controlled system currently connected with the actuator1. However, the above description is only one of the exemplaryembodiments of the present disclosure, but not limited thereto.

Refer back to FIG. 2 . After the step S20, the CPU 11 may tune theactuator 1 through the controlling module 111 by using the estimatedcontrol gain provided by the gain computing module 114 (step S22).

By using the tuning method of the present disclosure, the user doesn'thave to use additional computer software or to set the control gain ofthe actuator 1 following the guide given from the computer UI. Incomparison, all the user needs to do is to enable a correspondingparameter (such as to tick the auto-tuning parameter) of the actuator 1,and then the automatic gain tuning function may be activated for theactuator 1 to automatically complete the gain tuning procedure, which isvery convenient.

In one scenario, the actuator 1 may automatically complete the settingof multiple parameters after being tuned by the controlling module 111,so that the actuator 1 may control the controlled system to move stably.However, the CPU 11 of the present disclosure computes the estimatedcontrol gain based on the system inertia that is estimated, and thesystem inertia estimated in the step S20 may have an error in comparisonwith the actual system inertia of the controlled system. According tothe problem, the present disclosure may further test the actuator 1after the actuator 1 is tuned.

As shown in FIG. 2 , after the step S22, the actuator 1 being tuned mayinput a test signal to the controlled system (step S24), so that themotor 2 of the controlled system may perform operation. In theembodiment, the test signal mentioned above is corresponding to a squarewave current. The present disclosure makes the actuator 1 being tuned togenerate the square wave current to perturb the motor 2, so the presentdisclosure may confirm whether the operation of the controlled system isstable when the actuator 1 applies the expected bandwidth currentlyinquired. If the operation of the controlled system is stable, theactuator 1 may terminate the gain tuning procedure for this time (stepS26). If the operation of the controlled system is unstable (forexample, the controlled system vibes), the actuator 1 tunes theestimated control gain currently applied through the CPU 11 (detaileddescribed in the following).

Please refer to FIG. 1 , FIG. 2 , and FIG. 5 at the same time, whereinFIG. 5 is a flowchart for determining stability of an embodimentaccording to the present disclosure. As shown in FIG. 5 , after beingtuned based on the estimated control gain, the actuator 1 being tunedmay input the test signal to the controlled system (step S60). In themeantime, the motor 2 of the controlled system may be perturbed and thenperform operations accordingly, and the actuator 1 may determine whetherthe controlled system is stable while the motor 2 is operating (stepS62).

More specific, the test signal mentioned above is a pulse sent by theactuator 1 aimed at the controlled system, and the test signal may causethe controlled system (especially the motor 2) to perform a slightmovement. In one embodiment, the actuator 1 determines, in the step S62,whether the operation of the motor 2 causes unnecessary vibration to thecontrolled system after the actuator 1 applies a new control gain (i.e.,the estimated control gain) to control the controlled system.

If the controlled system is determined to be stable in the step S62, thetuning method of the present disclosure may be terminated and the gaintuning procedure of the actuator 1 may be completed.

If the controlled system is determined to be unstable in the step S62,the actuator 1 evaluates the unstable status of the controlled system bythe CPU 11, so as to determine whether the unstable status may beresolved by the actuator 1 through performing a resonance suppressionprocedure (step S64).

In particular, the bandwidth corresponding to the estimated control gaincomputed by the gain computing module 114 is known to the CPU 11. Also,the actuator 1 may monitor a vibration frequency of the controlledsystem under the unstable status. In the step S64, the CPU 11 maydirectly determine whether the unstable status of the controlled systemcan be resolved by the resonance suppression procedure in accordancewith the relationship between the bandwidth of the estimated controlgain and the vibration frequency of the controlled system.

If the controlled system is determined to be unstable where the unstablestatus may be resolved by the resonance suppression procedure, the CPU11 controls the actuator 1 to perform the resonance suppressionprocedure (step S66). In the embodiment, the CPU 11 restores thecontrolled system back to a stable status (e.g., no longer vibrate)through performing the resonance suppression procedure without retuningthe control gain of the actuator 1.

If the controlled system is determined to be unstable and the unstablestatus cannot be resolved through the resonance suppression procedure,it means that the estimated control gain computed by the gain computingmodule 114 is too high. In this scenario, the CPU 11 may lower thebandwidth corresponding to the estimated control gain computed by thegain computing module 114 (step S68).

After the step S68, the CPU 11 re-tunes the actuator 1 based on theestimated control gain with the lowered bandwidth, and then the CPU 11again determines whether the controlled system is stable through sameapproach as mentioned above (e.g., inputs the test signal) (step S70).If the controlled system is determined to be stable this time, the CPU11 terminates the tuning method of the present disclosure and completesthe gain tuning procedure of the actuator 1. If the controlled system isdetermined to be unstable, the CPU 11 re-executes the step S68 to againlower the bandwidth corresponding to the estimated control gain and thenre-tunes the actuator 1 in accordance with the estimated control gainwith the lowered bandwidth.

As mentioned above, the test signal sent out by the actuator 1 onlycause the controlled system (especially the motor 2) to slightly move,and the actuator 1 may determine whether the controlled system is stablebased on the slight movement of the motor 2. In one embodiment, whenperforming the tuning method of the present disclosure, the actuator 1only cause the motor 2 to rotate no more than one-tenth of a circle(i.e., smaller than or equal to 36 degrees). To sum up, the hardwarestructure of the controlled system being used incorporated with thetuning method of the present disclosure may be more flexible.

In order to successfully estimate the system inertia, the actuator 1must ensure that the motor 2 may generate a greater velocity responseduring the slight movement. Therefore, the actuator 1 may compute aneffective acceleration estimated value while the motor 2 moves andeventually estimate the system inertia correspondingly.

Please refer to FIG. 1 , FIG. 2 , FIG. 6 , and FIG. 7 at the same time,wherein FIG. 6 is an inertia estimating flowchart of an embodimentaccording to the present disclosure and FIG. 7 is a schematic diagramshowing a control architecture of an embodiment according to the presentdisclosure.

Before enabling the actuator 1 to perform the gain tuning procedure, theuser may set an initial control gain in accordance with thespecification of the motor 2 currently connected with the actuator 1,and the controlling module 111 of the CPU 11 may perform an initialsetting to the actuator 1 based on the initial control gain (step S40).In one embodiment, the initial control gain at least includes a positiongain being set based on the specification of the motor 2 for a positioncontroller 116 in the actuator 1 and a velocity gain being set based onthe specification of the motor 2 for the velocity controller 117 in theactuator 1.

As mentioned above, the present disclosure sets the initial control gainbased on the specification of the motor 2. After performing an initialsetting to the actuator 1 in accordance with the initial control gain,the actuator 1 may be used to test the controlled system. Therefore, thetuning result may not be affected by the original parameters (such asthe parameters randomly and arbitrarily set by the user) of the actuator1.

After the step S40, the actuator 1 after the initial setting may inputthe aforementioned sine wave current to the controlled system (step S42)so as to perturb the motor 2 (i.e., to cause the motor 2 performing aslight movement). In particular, the step S42 is similar to the step S10of FIG. 2 , detailed description is omitted here.

In order to shorten the estimated time of estimating the system inertia,the actuator 1 must control the motor 2 to complete the requiredmovement in a very short time. To do so, the frequency of the singlefrequency sine wave corresponding to the sine wave current may not betoo low. On the other hand, in order to prevent the motor 2 fromvibrating while performing the movement, the frequency of the singlefrequency sine wave corresponding to the sine wave current may not betoo high either (for example, may not be greater than a system resonancefrequency).

In one embodiment, the sine wave current may be corresponding to asingle frequency sine wave with a frequency range within 5 Hz to 15 Hz.In other words, the perturbed time of the motor 2 caused by the sinewave current is about 66 ms to 200 ms. However, the above description isonly one of the exemplary embodiments of the present disclosure, thefrequency of the single frequency sine wave may be smaller than 5 Hz orgreater than 15 Hz, and not limited within the above frequency range.

By setting the frequency range of the single frequency sine wave, theactuator 1 may shorten the estimated time of estimating the systeminertia, so that the execution time of the entire gain tuning proceduremay not exceed 1 second. Therefore, the efficiency of the actuator 1 maybe greatly improved.

As mentioned above, if a single frequency sine wave with a frequencythat is too small (e.g., smaller than 5 Hz) is used, the execution timeof the entire gain tuning procedure may be too long to satisfy the userdemand. In such circumstance, the actuator 1 may choose not to use anentire sine wave, so that the execution time of the gain tuningprocedure may still be reduced. However, the above description is onlyone of the exemplary embodiments, but not limited thereto.

After the step S42, the actuator 1 may use the current detectingcomponent 12, the torque estimating module 112, and the accelerationestimating module 113 to retrieve the current feedback signal and theposition feedback signal of the motor 2 while the motor 2 is operating,so as to compute the torque estimated value and the accelerationestimated value, and then estimate the system inertia of the controlledsystem by the gain computing module 114 (step S44).

As mentioned, the gain computing module 114 estimates the system inertiabased on the torque estimated value and the acceleration estimatedvalue. If the velocity response of the motor 2 is insufficient duringthe perturbed time, the actuator 1 may not correctly compute theacceleration estimated value of the motor 2 and may not estimate thesystem inertia.

In the embodiment, the CPU 11 determines whether the estimation for thesystem inertia is successful after the step S44 (step S46). If thesystem inertia is estimated successfully, the CPU 11 may continue therest part of the gain tuning procedure (step S50). For example, the CPU11 may continue to execute the step S20 to the step S26 as shown in FIG.2 , but not limited thereto.

If the CPU 11 determines in the step S46 that the estimation for thesystem inertia fails, the CPU 11 may then tune the initial control gainobtained in the step S40 based on the feedback information of the motor2 (e.g., the current feedback signal and the position feedback signal)and use the controlling module 111 to again perform the initial settingto the actuator 1 in accordance with the tuned initial control gain(step S48). Also, the CPU 11 re-executes the step S42 and the step S44for the actuator 1 being tuned to re-send the sine wave current to thecontrolled system and receive the feedback information from the motor 2for the estimation of the system inertia again.

More specific, the actuator 1 may input the sine wave current to thecontrolled system after the initial setting, then continually monitorthe movement of the motor 2 being perturbed, and then compute theacceleration estimated value based on the position feedback signal ofthe motor 2. In order for the actuator 1 to successfully compute theacceleration estimated value, the motor 2 should be able to perform alarge degree of movement in a very short time after being perturbed. Inorder to do so, the purpose of setting the content of the initialcontrol gain and the frequency of the single frequency sine wave of thepresent disclosure is for the motor 2 to reach its maximum accelerationcharacteristics while it moves. Accordingly, if different motors 2 areattached, the initial control gain and the single frequency sine wavemay be different.

As shown in FIG. 7 , the actuator 1 of the present disclosure furtherincludes a velocity estimating module 115, a position controller 116,and a velocity controller 117, wherein the velocity estimating module115, the position controller 116, and the velocity controller 117 may befirmware modules of the CPU 11, but not limited thereto.

As disclosed in FIG. 7 , when the controlled system (i.e., the motor 2and the load 3) operates, the position detecting component 22 may outputthe position feedback signal X. After receiving the position feedbacksignal X, the actuator 1 may return the position feedback signal X tothe position controller 116, the velocity estimating module 115 maycompute the velocity feedback signal V of the motor 2 based on theposition feedback signal X, and the velocity estimating module 115 maythen return the velocity feedback signal V to the velocity controller117.

The position controller 116 and the velocity controller 117 control thecontrolled system 4 based on the feedback signals, and the actuator 1may input the sine wave current 5 to the controlled system 4. Afterbeing perturbed by the sine wave current 5, the controlled system 4 mayoutput the current feedback signal I to the torque estimating module 112of the actuator 1 and output the position feedback signal X to theacceleration estimating module 113 of the actuator 1. Therefore, thetorque estimating module 112 may compute the torque estimated value Tbased on the current feedback signal I and the acceleration estimatedmodule 113 may compute the acceleration estimated value a based on theposition feedback signal X.

As mentioned above, if the actuator 1 cannot obtain an accelerationestimated value satisfied the requirement based on the movement of themotor 2, the step S48 of FIG. 6 should be executed to tune the initialcontrol gain, wherein the tuning of the initial control gain includestuning the position gain used by the position controller 116 and tuningthe velocity gain used by the velocity controller 117. In particular,the actuator 1 enlarges the velocity response of the controlled system 4under the frequency corresponding to the sine wave current 5 through thetuned initial control gain, so that the controlled system 4 may producethe acceleration that is large enough for satisfying the requirementafter receiving the sine wave current 5.

Please refer to FIG. 8 at the same time, wherein FIG. 8 is schematicdiagram showing frequency response of an embodiment according to thepresent disclosure. FIG. 8 discloses a response curve 6 of motor with noload of the controlled system 4 and also a response curve 7 of motorwith twenty times load of the controlled system 4.

As shown in the FIG. 8 , when the motor 2 is with no load, the highestamplification (40.37 dB) appears at the position corresponding to thefrequency of 20.5 Hz. When the motor 2 is with twenty times load, thehighest amplification (40.36 dB) appears at a position corresponding tothe frequency of 6.463 Hz. It should be mentioned that the aboveinformation may be regarded as known information by testing the motor 2after the motor 2 is manufactured.

According to the above information, the actuator 1 may choose a singlefrequency sine wave with a frequency between 6.4 Hz to 20.5 Hz togenerate the sine wave current 5 in the step S42 of FIG. 6 . In thisscenario, the motor 2, from no load to carrying twenty times load, maygenerate a greater velocity response when getting perturbed by the sinewave current 5 and therefore the actuator 1 could successfully computethe acceleration estimated value a of the motor 2.

If the CPU 11 determines in the step S46 as shown in the FIG. 6 that theestimation for the system inertia fails, it means that the load carriedby the motor 2 exceeds the aforementioned frequency range of the singlefrequency sine wave (for example, the motor 2 carries thirty timesload).

In particular, the amplification (i.e., the dB value) as shown in FIG. 8is depicted according to the velocity feedback and the position feedbackof the motor 2. In the step S48 of FIG. 6 , the CPU 11 of the actuator 1may tune the position gain used by the position controller 116 and thevelocity gain used by the velocity controller 117 based on the feedbacksignal of the motor 2, so as to enlarge the velocity response of themotor 2. Therefore, the actuator 1 may be assured in successfullyobtaining the velocity estimated value and estimating the system inertianext time when the sine wave current 5 is inputted to the controlledsystem 4.

By using the technical solution of the present disclosure, the actuatormay automatically complete the gain tuning procedure after beingactivated, wherein the execution time of the gain tuning procedure isshort, the motor doesn't have to perform a large degree of movement, andthe actuator doesn't have to store a large amount of data just for theexecution of the gain tuning procedure.

As the skilled person will appreciate, various changes and modificationscan be made to the described embodiment. It is intended to include allsuch variations, modifications and equivalents which fall within thescope of the present disclosure, as defined in the accompanying claims.

What is claimed is:
 1. A fast self-tuning method of gain, used by anactuator connected with a motor, comprising: a) retrieving a currentfeedback signal of the motor and computing a torque estimated valuebased on the current feedback signal; b) retrieving a position feedbacksignal of the motor and computing an acceleration estimated value basedon the position feedback signal; c) computing a system inertia inaccordance with the torque estimated value and the accelerationestimated value, wherein the system inertia is an inertia of the motorcarrying a load; d) computing an estimated control gain in accordancewith a no-load inertia of the motor and the system inertia; and e)tuning the actuator by using the estimated control gain.
 2. The fastself-tuning method in claim 1, further comprising: f) inputting a testsignal to a controlled system including the motor and the load by theactuator being tuned, wherein the test signal causes the motor toperform an operation; g) determining whether the controlled system isstable while the motor performs the operation; h) controlling theactuator to perform a resonance suppression procedure when thecontrolled system is determined to be under an unstable status where theunstable status can be resolved by the resonance suppression procedure;and i) lowering a bandwidth corresponded to the estimated control gainand re-tuning the actuator based on the estimated control gain with thelowered bandwidth when the controlled system is determined to be underthe unstable status and the unstable status cannot be resolved by theresonance suppression procedure.
 3. The fast self-tuning method in claim2, wherein the step h) and the step i) comprise determining whether theunstable status can be resolved by the resonance suppression procedurebased on a relationship between the bandwidth corresponded to theestimated control gain and a resonance frequency of the controlledsystem under the unstable status.
 4. The fast self-tuning method inclaim 2, further comprises a step a1): before the step a), inputting asine wave current to the controlled system to cause the motor tooperate, wherein the step a) comprises retrieving the current feedbacksignal while the motor operates, and the step b) comprise retrieving theposition feedback signal while the motor operates.
 5. The fastself-tuning method in claim 4, wherein the sine wave current iscorresponding to a single frequency sine wave within a frequency rangebetween 5 Hz to 15 Hz.
 6. The fast self-tuning method in claim 4,further comprising a step a0): before the step a1), performing aninitial setting to the actuator based on an initial control gain,wherein the initial control gain at least comprises a position gain anda velocity gain set in accordance with a specification of the motor,wherein the step a1) comprises inputting the sine wave current to thecontrolled system by the actuator after the initial setting.
 7. The fastself-tuning method in claim 6, further comprising: c1) after the stepc), determining whether the system inertia is successfully estimated;c2) when an estimation for the system inertia fails, tuning the initialcontrol gain and re-performing the initial setting to the actuator, andre-executing the step a0), the step a1), and the step a) to the step c);c3) when the estimation for the system inertial successes, executing thestep d) based on the system inertia.
 8. The fast self-tuning method inclaim 7, wherein the step c2) comprises tuning the position gain and thevelocity gain to enlarge a velocity response of the controlled systemunder the frequency corresponded to the sine wave current.
 9. The fastself-tuning method in claim 2, wherein the step c) comprises computingthe system inertia based on a first formula: ${J = \frac{T}{\alpha}},$wherein J is me system inertia, T is the torque estimated value, and ais the acceleration estimated value.
 10. The fast self-tuning method inclaim 2, wherein the step c) comprises executing a first-order linearregression calculation to generate a regression line based on the torqueestimated value and the acceleration estimated value of multiple timepoints and regarding a slope of the regression line as the systeminertia.
 11. The fast self-tuning method in claim 2, wherein theactuator comprises a bandwidth correspondence table, the bandwidthcorrespondence table records expected bandwidths respectivelycorresponding to different system inertias, and the system inertias areinversely proportional to the expected bandwidths; wherein, the step d)comprises inquiring the bandwidth correspondence table by the systeminertia to correspondingly obtain the expected bandwidth and decidingthe estimated control gain based on the expected bandwidth beingobtained.
 12. A servo actuator, electrically connected with a motor,wherein the motor carries a load, a controlled system is formed by themotor and the load, and the servo actuator comprising: a currentdetecting component, receiving an exciting current of the motor andgenerating a current feedback signal; a central processing unit (CPU),electrically connected with the current detecting component and themotor, and comprising: a torque estimating module, computing a torqueestimated value based on the current feedback signal; an accelerationestimating module, receiving a position feedback signal of the motor andcomputing an acceleration estimated value based on the position feedbacksignal; a gain computing module, computing a system inertiacorrespondingly based on the torque estimated value and the accelerationestimated value, and computing an estimated control gain based on ano-load inertia of the motor and the system inertia, wherein the systeminertia is an inertia of the motor carrying the load; and a controllingmodule, tuning the servo actuator based on the estimated control gain;and a storage, connected with the CPU, recording a data array includingthe torque estimated value and the acceleration estimated value, and theCPU is configured to read the data array to obtain the torque estimatedvalue and the acceleration estimated value.
 13. The servo actuator inclaim 12, wherein the CPU is configured to input a test signal to thecontrolled system by the servo actuator being tuned to cause the motorto perform an operation and to determine whether the controlled systemis stable while the motor performs the operation; wherein, the CPU isconfigured to perform a resonance suppression procedure when thecontrolled system is determined to be under an unstable status where theunstable status can be resolved by the resonance suppression procedure,and to lower a bandwidth corresponded to the estimated control gain andre-tune the actuator based on the estimated control gain with thelowered bandwidth when the unstable status cannot be resolved by theresonance suppression procedure.
 14. The servo actuator in claim 13,wherein the CPU is configured to input a sine wave current to thecontrolled system to cause the motor to operate, the torque estimatingmodule is configured to retrieve the current feedback signal while themotor operates, and the acceleration estimating module is configured toretrieve the position feedback signal while the motor operates.
 15. Theservo actuator in claim 14, wherein CPU is configured to generate thesine wave current based on a single frequency sine wave within afrequency range between 5 Hz to 15 Hz.
 16. The servo actuator in claim14, wherein the controlling module is configured to perform an initialsetting to the servo actuator based on an initial control gain, whereinthe initial control gain at least comprises a position gain and avelocity gain set in accordance with a specification of the motor, andthe CPU is configured to input the sine wave current to the controlledsystem by the servo actuator after the initial setting.
 17. The servoactuator in claim 16, wherein the CPU is configured to, when anestimation for the system inertia fails, tune the position gain and thevelocity gain of the initial control gain to enlarge a velocity responseof the controlled system under the frequency corresponded to the sinewave current, and re-perform the initial setting to the servo actuatorbased on the initial control gain being tuned.
 18. The servo actuator inclaim 13, wherein the gain computing module is configured to compute thesystem inertia in accordance with a first formula:${J = \frac{T}{\alpha}},$ wherein J is the system inertia, T is thetorque estimated value, and a is the acceleration estimated value. 19.The servo actuator in claim 13, wherein the torque estimating module andthe acceleration estimating module are configured to retrieve the torqueestimated value and the acceleration estimated value respectively atmultiple time points after the sine wave current is inputted by the CPUto the controlled system, and the gain computing module is configured toexecute a first-order linear regression calculation to generate aregression line based on multiple torque estimated value and multipleacceleration estimated value and regard a slope of the regression lineas the system inertia.
 20. The serve actuator in claim 13, wherein theservo actuator comprises a bandwidth correspondence table recordingexpected bandwidths respectively corresponding to different systeminertias, wherein the system inertias are inversely proportional to theexpected bandwidths, and the gain computing module is configured toinquire the bandwidth correspondence table by the system inertia tocorrespondingly obtain the expected bandwidth, and decide the estimatedcontrol gain based on the expected bandwidth being obtained.